Scenario: Node balancing cost optimization

The Optimization service provides you with the capability to optimize your orders to consider node balancing. You can prioritize node balancing over shipping costs when, for example, you want to satisfy high demand during peak shopping times.

E-commerce is in higher demand each year, especially during peak shopping seasons. During the holidays last year, your business had a high backlog in its stores because not all fulfillment dimensions were considered when an order was allocated to a specific store.

While e-commerce business grows, the Optimization service optimizes orders by considering all nodes (stores and distribution centers) for fulfillment. During peak times, you might want to prioritize network balancing and customer SLA over shipping costs. The Optimization service helps optimize orders to find the lowest cost to serve while still meeting customer expectations.

By using existing nodes and distribution centers to optimize order fulfillment, your business can meet the high e-commerce demand during peak shopping times. You can set business priorities to avoid a backlog, and the Optimization service optimizes each order to fulfill the order to avoid the backlog.

Capacity cost calculation is function of CapacityConsumed,

Node
Balancing Values

, Daily Capacity (Processing Plan), and

quantity
(input of Optimizer Call)

being optimized at ship nodes.

For more information, see the following definitions:

For example, if the configuration for Store1 and Store2 is includes the following costs:

Node ID	Backlog days	Tie breaker cost	Overcapacity penalty	Capacity (Processing plan)
Store1	0.9	0.2 USD	3.5 USD	30 units per day
Store2	1.1	0.2 USD	3 USD	40 units per day

Then, if the other costs such as shipping and processing are the same for Store1 and store2, the capacity cost drives the optimization decisions.

When the threshold is not reached

Demand is balanced based on the tie-breaker cost. See the following table to view the calculation.

The orders are allocated to Store1, then Store2, and again to Store1 until the threshold is reached. The Store1 and Store2 are of similar size and have the same tie-breaker cost. The same instance is at the network level where the demand is balanced across the network.

Note: Configure the node balancing calendar to control the balancing. You can set the threshold for regular days as less than one day, 2 days, or 3 days. Then, you can set the threshold higher for holidays and peak season to create demand balancing across the network.

Time series	Store1	Store2
T(1)	1 qty	1 qty
T(2)	1 qty	2 qty
T(3)	2 qty	2 qty
T(4)	2 qty	3 qty
T(N)	Reached threshold first as the daily capacity is lower	Might be still below the threshold

T(N) is greater than T(2) and T(2) is greater than T(1).
At time T, any order has 2 assignments for a specific order line.

Time series	Store1	Store2	Optimization result	Comments
T(1)	`CapacityConsumed` = 1 CCU = 0.03333 `CapacityCost` = 0.000222	`CapacityConsumed` = 1 CCU = 0.025 `CapacityCost` = 0.000125	Store2	Only tiebreaker cost is contributing to the capacity cost. Since it is the same at nodes, CCU becomes the driving factor.
T(2)	`CapacityConsumed` = 1 CCU = 0.03333 `CapacityCost` = 0.000222	`CapacityConsumed` = 2 CCU = 0.050 `CapacityCost` = 0.0005	Store1	Since the demand is allocated to Store2, Order Management System (OMS) should provide the CapacityConsumed as 2 for Store2
T(3)	`CapacityConsumed` = 2 CCU = 0.0666 `CapacityCost` = 0.000222	`CapacityConsumed` = 2 CCU = 0.050 `CapacityCost` = 0.0005	Store2	Observe how the demand is balancing, currently the demand is allocated to Store1. This cycle of balancing continues as the average utilization increases across the stores.

This demand balancing continues until one of the ship nodes reaches the threshold.

If the tiebreaker of Store2 is higher, for example, 0.5 USD, then the initial allocations apply to Store1 only until the full utilization is comparable to the Store2 cost. The pattern of demand allocation between the stores is different in such cases. For

When the threshold value is reached

For the same example in Example, CapacityConsumed values are applied to depict the effect of load balancing. The value might not represent the actual demand allocation based on the node balancing calendar values that are configured.

Time series	Store1	Store2	Optimization result	Comments
T(1)	`CapacityConsumed` = 33 CCU = 1.1 `CapacityCost` = 4.2605	`CapacityConsumed` = 42 CCU = 1.05 `CapacityCost` = 0.055125	Store2	As Store2 is below the threshold and the Store1crosses the threshold, the penalty is applied at Store1.
T(2)	`CapacityConsumed` = 65 CCU = 2.2 `CapacityCost` = 8.157	`CapacityConsumed` = 48 CCU = 1.2 `CapacityCost` = 3.372	Store2	Both cross the threshold, however, Store1 has more backlog.

Note: Store1 has CapacityCost of 8.157 USD as compared to 4.2605 USD for CCU of 2.2 and in T(1) and T(2) that is the penalty that is applied per the unit of backlog.